{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\akshayaj\Box\NHTSAnalysis\Logs/CausalNHTS.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}20 Sep 2024, 22:43:57
{txt}
{com}. 
. local year = 2017
{txt}
{com}. 
. 
. 
. 
. 
. 
. // local outcome_vars = "num_new_vehweighted single_vehicle_mean_ageweighted multi_vehicle_mean_ageweighted max_veh_ageweighted min_milesweighted multi_vehicle_num_vehiclesweight"
. local outcome_vars = "single_vehicle_mean_ageweighted multi_vehicle_mean_ageweighted multi_vehicle_num_vehiclesweight num_new_vehweighted max_veh_ageweighted min_milesweighted num_vehiclesweighted num_newly_bought_vehweighted sum_total_milesweighted oldest_veh_travelweighted all_hh_new_vehweighted all_hh_newly_bought_vehweighted"
{txt}
{com}. 
. local i = 0
{txt}
{com}. foreach year of num 2017 2009{c -(}
{txt}  2{com}.         clear
{txt}  3{com}.         
.         if(`year'==2017){c -(}
{txt}  4{com}.                 local ind_vars = "hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted"
{txt}  5{com}.         {c )-}
{txt}  6{com}.         else{c -(}
{txt}  7{com}.                 local ind_vars = "hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted"
{txt}  8{com}.         {c )-}
{txt}  9{com}.         
.         import delimited "CleanData/NHTS`year'.csv"
{txt} 10{com}.         gen nosafetyweighted = 1-hassafetyweighted
{txt} 11{com}.         drop if treatmentyearweighted>=(`year'-2) & treatmentyearweighted<=(`year'+2)
{txt} 12{com}.         
.         
. 
. //      local treat_var = "hassafetyweighted"
.         local treat_var = "nosafetyweighted"
{txt} 13{com}. 
.         gen x = 0
{txt} 14{com}.         gen y = 0
{txt} 15{com}. 
.         
. 
.         local j = 0
{txt} 16{com}.         local out_vars = ""
{txt} 17{com}.         
.         reg y x 
{txt} 18{com}.         est sto model`i'
{txt} 19{com}.         
.         foreach outcome_var in `outcome_vars'{c -(}
{txt} 20{com}.                 
.                 if("`outcome_var'"=="num_new_vehweighted" | "`outcome_var'"=="all_hh_new_vehweighted" | "`outcome_var'"=="all_hh_newly_bought_vehweighted"){c -(}
{txt} 21{com}.                         local floatFormat = "%4.3f"
{txt} 22{com}.                 {c )-}
{txt} 23{com}.                 else{c -(}
{txt} 24{com}.                         local floatFormat = "%4.2f"
{txt} 25{com}.                 {c )-}
{txt} 26{com}.                 
.                 di "`outcome_var'"
{txt} 27{com}.                 teffects psmatch (`outcome_var') (`treat_var' `ind_vars'), base
{txt} 28{com}.                 di e(cmdline)
{txt} 29{com}.                 ereturn list
{txt} 30{com}.                 
.                 local tempMean = string(round(e(b)[1,1], .001), "`floatFormat'")
{txt} 31{com}.                 local tempSD = string(round(sqrt(e(V)[1,1]), .001), "`floatFormat'")
{txt} 32{com}.                 local tempT = e(b)[1,1]/sqrt(e(V)[1,1])
{txt} 33{com}.                 local tempP = normal(-abs(`tempT'))*2
{txt} 34{com}.                 
.                 if(`tempP'<0.01){c -(}
{txt} 35{com}.                         local tempStars = "***"
{txt} 36{com}.                 {c )-} 
{txt} 37{com}.                 else if(`tempP'<0.05){c -(}
{txt} 38{com}.                         local tempStars = "**"
{txt} 39{com}.                 {c )-} 
{txt} 40{com}.                 else if(`tempP'<0.1){c -(}
{txt} 41{com}.                         local tempStars = "*"
{txt} 42{com}.                 {c )-} 
{txt} 43{com}.                 else{c -(}
{txt} 44{com}.                         local tempStars = ""
{txt} 45{com}.                 {c )-}
{txt} 46{com}.                 
.                 
.                 
.                 local prefix = "\makecell{c -(}"
{txt} 47{com}.                 local suffix = "{c )-}"
{txt} 48{com}.                                 
.                 local tempEntry = "`prefix'"+"`tempMean'`tempStars' \nextline (`tempSD')"+"`suffix'"
{txt} 49{com}.                 est res model`i'
{txt} 50{com}.                 estadd local var`j' = "`tempEntry'"
{txt} 51{com}.                 local out_vars = "`out_vars' var`j'"
{txt} 52{com}.                 local j = `j'+1
{txt} 53{com}.                 
.         {c )-}
{txt} 54{com}.         
.         local i = `i'+1
{txt} 55{com}. {c )-}
{res}{txt}(encoding automatically selected: ISO-8859-1)
{res}{text}(37 vars, 51 obs)
(1 observation deleted)
{p 0 6 2}note: {bf:x} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}        50
{txt}{hline 13}{c +}{hline 34}   F(0, 49)        = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0        49           0   {txt}R-squared       ={res}         .
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}         .
{txt}       Total {c |} {res}          0        49           0   {txt}Root MSE        =   {res}      0

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           y{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}x {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 7}_cons {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}single_vehicle_mean_ageweighted

{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}single_vehicle~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .8149942{col 30}{space 2} .2134534{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .3966331{col 71}{space 3} 1.233355
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (single_vehicle_mean_ageweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (single_vehicle_mean_ageweighted) (nosafetyweighted hhsizew{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}single_vehicle_mean_ageweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}single_vehicle_mean_ageweighted nosafetyweighted hhsizeweighted drvrcntweigh{txt}.."
      e(datasignature) : "{res}50:10:3049593412:2668042368{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var0) : "{res:\makecell{0.82*** \nextline (0.21)}}"
multi_vehicle_mean_ageweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}multi_vehicle_~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .9960611{col 30}{space 2} .1924572{col 41}{space 1}    5.18{col 50}{space 3}0.000{col 58}{space 4} .6188518{col 71}{space 3}  1.37327
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (multi_vehicle_mean_ageweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (multi_vehicle_mean_ageweighted) (nosafetyweighted hhsizewe{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}multi_vehicle_mean_ageweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}multi_vehicle_mean_ageweighted nosafetyweighted hhsizeweighted drvrcntweight{txt}.."
      e(datasignature) : "{res}50:10:3790461411:1122515279{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var1) : "{res:\makecell{1.00*** \nextline (0.19)}}"
multi_vehicle_num_vehiclesweight
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}multi_vehicle_~t{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .1322746{col 30}{space 2}  .040532{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0528334{col 71}{space 3} .2117158
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (multi_vehicle_num_vehiclesweight) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (multi_vehicle_num_vehiclesweight) (nosafetyweighted hhsize{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}multi_vehicle_num_vehiclesweight{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}multi_vehicle_num_vehiclesweight nosafetyweighted hhsizeweighted drvrcntweig{txt}.."
      e(datasignature) : "{res}50:10:340582803:4015522999{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var2) : "{res:\makecell{0.13*** \nextline (0.04)}}"
num_new_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}num_new_vehwei~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-.0052657{col 30}{space 2} .0026401{col 41}{space 1}   -1.99{col 50}{space 3}0.046{col 58}{space 4}-.0104401{col 71}{space 3}-.0000912
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (num_new_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (num_new_vehweighted) (nosafetyweighted hhsizeweighted drvr{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}num_new_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}num_new_vehweighted nosafetyweighted hhsizeweighted drvrcntweighted incomewe{txt}.."
      e(datasignature) : "{res}50:10:3158282587:1980312717{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var3) : "{res:\makecell{-0.005** \nextline (0.003)}}"
max_veh_ageweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}max_veh_agewei~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} 1.450991{col 30}{space 2} .3209027{col 41}{space 1}    4.52{col 50}{space 3}0.000{col 58}{space 4} .8220334{col 71}{space 3} 2.079949
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (max_veh_ageweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (max_veh_ageweighted) (nosafetyweighted hhsizeweighted drvr{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}max_veh_ageweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}max_veh_ageweighted nosafetyweighted hhsizeweighted drvrcntweighted incomewe{txt}.."
      e(datasignature) : "{res}50:10:933391600:1581828112{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var4) : "{res:\makecell{1.45*** \nextline (0.32)}}"
min_milesweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}min_milesweigh~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-1219.546{col 30}{space 2}  352.579{col 41}{space 1}   -3.46{col 50}{space 3}0.001{col 58}{space 4}-1910.588{col 71}{space 3}-528.5035
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (min_milesweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (min_milesweighted) (nosafetyweighted hhsizeweighted drvrcn{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}min_milesweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}min_milesweighted nosafetyweighted hhsizeweighted drvrcntweighted incomeweig{txt}.."
      e(datasignature) : "{res}50:10:3398581352:2939492302{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var5) : "{res:\makecell{-1219.55*** \nextline (352.58)}}"
num_vehiclesweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}num_vehicleswe~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .1597361{col 30}{space 2} .0348044{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4} .0915207{col 71}{space 3} .2279515
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (num_vehiclesweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (num_vehiclesweighted) (nosafetyweighted hhsizeweighted drv{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}num_vehiclesweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}num_vehiclesweighted nosafetyweighted hhsizeweighted drvrcntweighted incomew{txt}.."
      e(datasignature) : "{res}50:10:107246294:1364833888{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var6) : "{res:\makecell{0.16*** \nextline (0.04)}}"
num_newly_bought_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}num_newly_boug~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .0153638{col 30}{space 2} .0118028{col 41}{space 1}    1.30{col 50}{space 3}0.193{col 58}{space 4}-.0077693{col 71}{space 3} .0384969
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (num_newly_bought_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (num_newly_bought_vehweighted) (nosafetyweighted hhsizeweig{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}num_newly_bought_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}num_newly_bought_vehweighted nosafetyweighted hhsizeweighted drvrcntweighted{txt}.."
      e(datasignature) : "{res}50:10:458945202:3034338823{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var7) : "{res:\makecell{0.01 \nextline (0.01)}}"
sum_total_milesweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}sum_total_mile~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-152.1085{col 30}{space 2}  491.951{col 41}{space 1}   -0.31{col 50}{space 3}0.757{col 58}{space 4}-1116.315{col 71}{space 3} 812.0978
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (sum_total_milesweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (sum_total_milesweighted) (nosafetyweighted hhsizeweighted {txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}sum_total_milesweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}sum_total_milesweighted nosafetyweighted hhsizeweighted drvrcntweighted inco{txt}.."
      e(datasignature) : "{res}50:10:3720508245:941023990{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var8) : "{res:\makecell{-152.11 \nextline (491.95)}}"
oldest_veh_travelweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}oldest_veh_tra~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-1680.719{col 30}{space 2} 608.0839{col 41}{space 1}   -2.76{col 50}{space 3}0.006{col 58}{space 4}-2872.542{col 71}{space 3}-488.8965
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (oldest_veh_travelweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (oldest_veh_travelweighted) (nosafetyweighted hhsizeweighte{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}oldest_veh_travelweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}oldest_veh_travelweighted nosafetyweighted hhsizeweighted drvrcntweighted in{txt}.."
      e(datasignature) : "{res}50:10:2537986941:3483051322{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
               e(var9) : "{res:\makecell{-1680.72*** \nextline (608.08)}}"
all_hh_new_vehweighted
{res}{txt}{p 0 6 2}note: variance correction results in a negative variance estimate; ignoring the correction term{p_end}

Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}all_hh_new_veh~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-.0042241{col 30}{space 2} .0074646{col 41}{space 1}   -0.57{col 50}{space 3}0.571{col 58}{space 4}-.0188544{col 71}{space 3} .0104062
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (all_hh_new_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (all_hh_new_vehweighted) (nosafetyweighted hhsizeweighted d{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}all_hh_new_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}all_hh_new_vehweighted nosafetyweighted hhsizeweighted drvrcntweighted incom{txt}.."
      e(datasignature) : "{res}50:10:299588085:118450788{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
              e(var10) : "{res:\makecell{-0.004 \nextline (0.007)}}"
all_hh_newly_bought_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        50
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}all_hh_newly_b~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .0177091{col 30}{space 2} .0105975{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0030617{col 71}{space 3} .0384799
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (all_hh_newly_bought_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted youngchildweighted ageweighted), base

scalars:
                  e(N) =  {res}50
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}34
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (all_hh_newly_bought_vehweighted) (nosafetyweighted hhsizew{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}all_hh_newly_bought_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}all_hh_newly_bought_vehweighted nosafetyweighted hhsizeweighted drvrcntweigh{txt}.."
      e(datasignature) : "{res}50:10:2325852941:1835557083{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 9 x 9
                {txt}e(bps) : {res} 1 x 9

{txt}functions:
             e(sample)   
(results {stata estimates replay model0:model0} are active now)

added macro:
              e(var11) : "{res:\makecell{0.018* \nextline (0.011)}}"
{res}{txt}(encoding automatically selected: ISO-8859-1)
{res}{text}(37 vars, 51 obs)
(2 observations deleted)
{p 0 6 2}note: {bf:x} omitted because of collinearity.{p_end}

      Source {c |}       SS           df       MS      Number of obs   ={res}        49
{txt}{hline 13}{c +}{hline 34}   F(0, 48)        = {res}     0.00
{txt}       Model {c |} {res}          0         0           .   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0        48           0   {txt}R-squared       ={res}         .
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}         .
{txt}       Total {c |} {res}          0        48           0   {txt}Root MSE        =   {res}      0

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           y{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}x {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 7}_cons {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}single_vehicle_mean_ageweighted

{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}single_vehicle~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} 1.050993{col 30}{space 2} .3687287{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .3282977{col 71}{space 3} 1.773688
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (single_vehicle_mean_ageweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (single_vehicle_mean_ageweighted) (nosafetyweighted hhsizew{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}single_vehicle_mean_ageweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}single_vehicle_mean_ageweighted nosafetyweighted hhsizeweighted drvrcntweigh{txt}.."
      e(datasignature) : "{res}49:9:51071771:228102266{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var0) : "{res:\makecell{1.05*** \nextline (0.37)}}"
multi_vehicle_mean_ageweighted
{res}{txt}{p 0 6 2}note: variance correction results in a negative variance estimate; ignoring the correction term{p_end}

Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}multi_vehicle_~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .7031077{col 30}{space 2} .4610893{col 41}{space 1}    1.52{col 50}{space 3}0.127{col 58}{space 4}-.2006108{col 71}{space 3} 1.606826
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (multi_vehicle_mean_ageweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (multi_vehicle_mean_ageweighted) (nosafetyweighted hhsizewe{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}multi_vehicle_mean_ageweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}multi_vehicle_mean_ageweighted nosafetyweighted hhsizeweighted drvrcntweight{txt}.."
      e(datasignature) : "{res}49:9:13846297:2786468894{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var1) : "{res:\makecell{0.70 \nextline (0.46)}}"
multi_vehicle_num_vehiclesweight
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}multi_vehicle_~t{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .0859398{col 30}{space 2} .0171366{col 41}{space 1}    5.01{col 50}{space 3}0.000{col 58}{space 4} .0523526{col 71}{space 3}  .119527
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (multi_vehicle_num_vehiclesweight) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (multi_vehicle_num_vehiclesweight) (nosafetyweighted hhsize{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}multi_vehicle_num_vehiclesweight{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}multi_vehicle_num_vehiclesweight nosafetyweighted hhsizeweighted drvrcntweig{txt}.."
      e(datasignature) : "{res}49:9:3955129635:2984674408{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var2) : "{res:\makecell{0.09*** \nextline (0.02)}}"
num_new_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}num_new_vehwei~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-.0098355{col 30}{space 2} .0046922{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.0190321{col 71}{space 3}-.0006389
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (num_new_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (num_new_vehweighted) (nosafetyweighted hhsizeweighted drvr{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}num_new_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}num_new_vehweighted nosafetyweighted hhsizeweighted drvrcntweighted incomewe{txt}.."
      e(datasignature) : "{res}49:9:1960277135:1583456000{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var3) : "{res:\makecell{-0.010** \nextline (0.005)}}"
max_veh_ageweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}max_veh_agewei~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} 1.274442{col 30}{space 2} .0457939{col 41}{space 1}   27.83{col 50}{space 3}0.000{col 58}{space 4} 1.184687{col 71}{space 3} 1.364196
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (max_veh_ageweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (max_veh_ageweighted) (nosafetyweighted hhsizeweighted drvr{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}max_veh_ageweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}max_veh_ageweighted nosafetyweighted hhsizeweighted drvrcntweighted incomewe{txt}.."
      e(datasignature) : "{res}49:9:3897577000:4210471139{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var4) : "{res:\makecell{1.27*** \nextline (0.05)}}"
min_milesweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}min_milesweigh~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-394.4711{col 30}{space 2} 209.7487{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4} -805.571{col 71}{space 3} 16.62879
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (min_milesweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (min_milesweighted) (nosafetyweighted hhsizeweighted drvrcn{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}min_milesweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}min_milesweighted nosafetyweighted hhsizeweighted drvrcntweighted incomeweig{txt}.."
      e(datasignature) : "{res}49:9:3215404966:2707890815{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var5) : "{res:\makecell{-394.47* \nextline (209.75)}}"
num_vehiclesweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}num_vehicleswe~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} .0964655{col 30}{space 2} .0272158{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0431235{col 71}{space 3} .1498074
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (num_vehiclesweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (num_vehiclesweighted) (nosafetyweighted hhsizeweighted drv{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}num_vehiclesweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}num_vehiclesweighted nosafetyweighted hhsizeweighted drvrcntweighted incomew{txt}.."
      e(datasignature) : "{res}49:9:468238150:500291946{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var6) : "{res:\makecell{0.10*** \nextline (0.03)}}"
num_newly_bought_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}num_newly_boug~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-.0177456{col 30}{space 2} .0064072{col 41}{space 1}   -2.77{col 50}{space 3}0.006{col 58}{space 4}-.0303035{col 71}{space 3}-.0051877
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (num_newly_bought_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (num_newly_bought_vehweighted) (nosafetyweighted hhsizeweig{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}num_newly_bought_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}num_newly_bought_vehweighted nosafetyweighted hhsizeweighted drvrcntweighted{txt}.."
      e(datasignature) : "{res}49:9:3573417527:3729756001{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var7) : "{res:\makecell{-0.02*** \nextline (0.01)}}"
sum_total_milesweighted
{res}{txt}{p 0 6 2}note: variance correction results in a negative variance estimate; ignoring the correction term{p_end}

Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}sum_total_mile~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2} 415.6768{col 30}{space 2} 684.1917{col 41}{space 1}    0.61{col 50}{space 3}0.543{col 58}{space 4}-925.3142{col 71}{space 3} 1756.668
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (sum_total_milesweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (sum_total_milesweighted) (nosafetyweighted hhsizeweighted {txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}sum_total_milesweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}sum_total_milesweighted nosafetyweighted hhsizeweighted drvrcntweighted inco{txt}.."
      e(datasignature) : "{res}49:9:3659988643:956617398{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var8) : "{res:\makecell{415.68 \nextline (684.19)}}"
oldest_veh_travelweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}oldest_veh_tra~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-461.1934{col 30}{space 2} 293.1358{col 41}{space 1}   -1.57{col 50}{space 3}0.116{col 58}{space 4}-1035.729{col 71}{space 3} 113.3422
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (oldest_veh_travelweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (oldest_veh_travelweighted) (nosafetyweighted hhsizeweighte{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}oldest_veh_travelweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}oldest_veh_travelweighted nosafetyweighted hhsizeweighted drvrcntweighted in{txt}.."
      e(datasignature) : "{res}49:9:3665942418:2539088885{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
               e(var9) : "{res:\makecell{-461.19 \nextline (293.14)}}"
all_hh_new_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}all_hh_new_veh~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-.0084764{col 30}{space 2} .0041558{col 41}{space 1}   -2.04{col 50}{space 3}0.041{col 58}{space 4}-.0166217{col 71}{space 3}-.0003311
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (all_hh_new_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (all_hh_new_vehweighted) (nosafetyweighted hhsizeweighted d{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}all_hh_new_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}all_hh_new_vehweighted nosafetyweighted hhsizeweighted drvrcntweighted incom{txt}.."
      e(datasignature) : "{res}49:9:1310804481:4051873444{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
              e(var10) : "{res:\makecell{-0.008** \nextline (0.004)}}"
all_hh_newly_bought_vehweighted
{res}
{txt}Treatment-effects estimation{col 48}Number of obs {col 67}= {res}        49
{txt:Estimator}{col 16}:{res: propensity-score matching}{col 48}{txt:Matches: requested }{col 67}{txt:=}          1
{txt:Outcome model}{col 16}:{res: matching}{txt}{col 63}min {col 67}= {res}         1
{txt:Treatment model}{col 16}:{res: logit}{col 63}{txt:max }{col 67}{txt:=}          1
{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}   AI robust
{col 1}all_hh_newly_b~d{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      z{col 50}   P>|z|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}ATE              {txt}{c |}
nosafetyweighted {c |}
{space 7}(1 vs 0)  {c |}{col 18}{res}{space 2}-.0145707{col 30}{space 2} .0058399{col 41}{space 1}   -2.50{col 50}{space 3}0.013{col 58}{space 4}-.0260167{col 71}{space 3}-.0031247
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
teffects psmatch (all_hh_newly_bought_vehweighted) (nosafetyweighted hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweighted numadltweighted ageweighted), base

scalars:
                  e(N) =  {res}49
                 {txt}e(n0) =  {res}16
                 {txt}e(n1) =  {res}33
            {txt}e(caliper) =  {res}.
            {txt}e(treated) =  {res}1
            {txt}e(control) =  {res}0
        {txt}e(k_nneighbor) =  {res}1
            {txt}e(k_nnmin) =  {res}1
            {txt}e(k_nnmax) =  {res}1
           {txt}e(k_robust) =  {res}2
           {txt}e(k_levels) =  {res}2

{txt}macros:
                e(cmd) : "{res}teffects{txt}"
            e(cmdline) : "{res}teffects psmatch (all_hh_newly_bought_vehweighted) (nosafetyweighted hhsizew{txt}.."
            e(predict) : "{res}teffects_p{txt}"
          e(estat_cmd) : "{res}teffects_estat{txt}"
       e(marginsnotok) : "{res}_ALL{txt}"
             e(depvar) : "{res}all_hh_newly_bought_vehweighted{txt}"
               e(tvar) : "{res}nosafetyweighted{txt}"
             e(subcmd) : "{res}psmatch{txt}"
             e(tmodel) : "{res}logit{txt}"
               e(stat) : "{res}ate{txt}"
              e(title) : "{res}Treatment-effects estimation{txt}"
            e(tlevels) : "{res}0 1{txt}"
          e(psvarlist) : "{res}hhsizeweighted drvrcntweighted incomeweighted hbppopdnweighted wrkcountweigh{txt}.."
                e(vce) : "{res}robust{txt}"
            e(vcetype) : "{res}AI robust{txt}"
  e(datasignaturevars) : "{res}all_hh_newly_bought_vehweighted nosafetyweighted hhsizeweighted drvrcntweigh{txt}.."
      e(datasignature) : "{res}49:9:1848371731:1857011780{txt}"
         e(properties) : "{res}b V{txt}"

matrices:
                  e(b) : {res} 1 x 1
                  {txt}e(V) : {res} 1 x 1
                {txt}e(Vps) : {res} 8 x 8
                {txt}e(bps) : {res} 1 x 8

{txt}functions:
             e(sample)   
(results {stata estimates replay model1:model1} are active now)

added macro:
              e(var11) : "{res:\makecell{-0.015** \nextline (0.006)}}"

{com}. 
. esttab model1 model0 using "Tables/causal-NHTS.tex", drop(*) stats(`out_vars', labels("\makecell{c -(}Single-Vehicle Household \nextline Vehicle Age{c )-}" "\makecell{c -(}Multi-Vehicle Household \nextline Vehicle Age{c )-}" "\makecell{c -(}Multi-Vehicle Households \nextline Vehicle Count{c )-}" "\makecell{c -(}Vehicle-Owning Households \nextline New Vehicles Count{c )-}" "\makecell{c -(}Vehicle-Owning Households \nextline Maximum Vehicle Age{c )-}" "\makecell{c -(}Vehicle-Owning Households \nextline Minimum Self-Reported Annual VMT{c )-}" "\makecell{c -(}All Households \nextline Vehicle Count{c )-}" "\makecell{c -(}Vehicle-Owning Households \nextline Newly-Purchased Vehicle Count{c )-}" "\makecell{c -(}All Households \nextline Self-Reported Aggregate Household VMT{c )-}" "\makecell{c -(}Vehicle-Owning Households \nextline Oldest Vehicle Self-Reported Annual VMT{c )-}" "\makecell{c -(}All Households \nextline New Vehicles Count{c )-}" "\makecell{c -(}All Households \nextline Newly-Purchased Vehicle Count{c )-}")) nostar mtitles("NHTS 2009" "NHTS 2017") nonumbers not nolines  replace sub(\_ _) align(l|ll)
{res}{txt}(output written to {browse  `"Tables/causal-NHTS.tex"'})

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\akshayaj\Box\NHTSAnalysis\Logs/CausalNHTS.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}20 Sep 2024, 22:44:10
{txt}{.-}
{smcl}
{txt}{sf}{ul off}